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In silico modeling helps predict severity of mitochondrial disease
Date:1/27/2008

re both essential for this study. The experiments gave us new information that we had to have to build the simulation, and the simulation was used as a tool to analyze the data from the experiment.

Dr. Patrick Chinnery, Wellcome Senior Fellow in Clinical Science and professor of neurogenetics at the University of Newcastle in the United Kingdom, remarked: Mitochondrial disease can have devastating effects on a family, and the chance of having affected children is a cause of major stress. By defining the main biological mechanism, we hope in the long term to develop counseling guidelines that will help patients and their families make more informed decisions.

The computational model reveals how mtDNA is divided into different embryonic cells before and after implantation and how the replicating mtDNA molecules are subsequently separated between the dividing germ cells that make up the embryo. The model accounts for the marked reduction in the number of mtDNA molecules that are transmitted from mother to offspring, the so-called mitochondrial genetic bottleneck. It is thought that this genetic bottleneck has evolved over time to remove deleterious mitochondrial mutations from the population. These mutations are either lost during transmission or, if transferred, give rise to offspring with a low chance of survival.

Although the current study investigates the transmission of mitochondrial DNA in mice, the computational model is also applicable to human data. Mitochondrial diseases are thought to affect as many as one person in 5000. The research offers the hope that clinicians will be able to predict a childs risk of developing maternally inherited mitochondrial diseases that cause muscle weakness, diabetes, stroke, heart failure and epilepsy.


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Contact: Barry Whyte
whyte@vbi.vt.edu
540-231-1767
Virginia Tech
Source:Eurekalert

Page: 1 2

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